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Accelerating model deployment: 100X faster dev loops with development deployments

Baseten's development deployments speed up ML model dev loops, replacing slow workflows with a live reload system for quick, seconds-long testing updates.

New in October: Find community with The DSC

October was a big month for the ML industry, with more momentum than ever behind spooky-good models and novel applications

New in September: Increasing flexibility and robustness

The state of cutting-edge open-source ML models, a more flexible interface for invoking models, and robust application development workflows

New in August: Deploy, deploy, deploy

In August, we focused on model deployment, from basic classifiers to advanced Stable Diffusion image generators, as a key step in realizing ML's business value.

Why we built and open-sourced a model serving solution

Truss, our open-sourced bridge for model development to deployment, saves time for data scientists and ML engineers on MLOps tasks in model serving.

New in July: A seamless bridge from model development to deployment

We've launched Truss, an OSS Python package for model serving and deployment. Baseten users have been using it unknowingly, now offering new capabilities.

New in June: Full-stack superpowers

Excited to highlight this month's major strides in empowering data scientists to create and maintain full-stack applications with real value.

New in May 2022: Off-site but on-track

In late April, we launched Baseten's public beta and new brand, now focusing on learning and enhancing the product for beta users like you!

Go from machine learning models to full-stack applications

Introducing Baseten, an ML Application Builder for Data Scientists